We are seeking a Senior MLOps / AI Engineer with hands-on experience in building, deploying, and operating scalable AI/ML and Generative AI platforms. This role will focus on MLOps, LLMOps, and Agentic AI Operations, including end-to-end ML pipelines, model deployment automation, LLM lifecycle management, RAG pipelines, vector databases, MCP servers, and multi-agent orchestration environments.
Focus Areas: MLOps, LLMOps, Agentic AI Ops, AI Platform Engineering
Experience: 8-10 years
Location: Remote / Hybrid / Onsite
Employment Type: Full-time
Key Responsibilities
AI Platform & MLOps
- Build end-to-end ML pipelines (ingestion → deployment → monitoring)
- Automate training, validation, deployment, retraining via CI/CD
- Manage feature stores, versioning, experiment tracking
- Deploy batch & real-time models; design scalable GPU/cloud infra
- Monitor performance, drift, latency; enable continuous retraining
LLMOps & Generative AI
- Manage LLM lifecycle (prompting, versioning, fine-tuning, deployment)
- Build RAG pipelines (embeddings, vector DBs, retrieval, reranking)
- Handle embeddings, chunking, semantic search, index updates
- Integrate OpenAI, Claude, Bedrock, Ollama
- Evaluate accuracy, safety, hallucination, latency, cost
Agentic AI Systems
- Design multi-agent systems for automation & decision-making
- Use LangChain, LangGraph, MCP; integrate APIs, DBs, tools
- Implement guardrails, human-in-loop, logging, observability
- Scale orchestration layers, vector DBs, AI workflows
CI/CD, DevSecOps & Governance
- Build CI/CD (GitHub Actions, Jenkins, ArgoCD) with testing & security
- Ensure secure, reproducible deployments across environments
- Implement monitoring, auditability, compliance, documentation
- Track metrics (drift, cost, latency, errors, usage)
- Support responsible AI (bias, explainability, safety)
Required Skills and Experience
- 8-10 years of hands-on experience in MLOps, AI engineering, data engineering, DevOps, platform engineering, or cloud-native AI systems.
- Strong programming experience with Python.
- Hands-on experience with CI/CD tools such as:
- o GitHub Actions
- o Jenkins
- o ArgoCD
- Experience with AWS AI/ML services
Preferred Qualifications
- Experience with LLMOps, prompt lifecycle management, and LLM evaluation frameworks.
- Experience building and operating agentic AI workflows using tool calling, planning, memory, and orchestration patterns.
- Familiarity with GPU-based workloads and distributed model serving.
- Experience with infrastructure-as-code tools such as Terraform or CloudFormation.
- Experience with observability tools such as Prometheus, Grafana, CloudWatch, ELK, Datadog, New Relic, or LangSmith.
Pay: ₹300,000.00 - ₹1,500,000.00 per year
Work Location: In person
